Systems and methods for determining respiration metrics

ABSTRACT

Systems, devices and methods provide for acquiring respiration information. A respiration information device includes timer circuitry to time a plurality of shorter time apertures and a plurality of longer time apertures. A respiration sensor, which may be implemented as a transthoracic impedance sensor, is configured to generate a signal indicative of patient respiration. For each aperture of the plurality of shorter time apertures and for each aperture of the plurality of longer time apertures, an estimated characteristic of the respiration is determined. Respiration metrics are developed using one or both of the estimated respiration characteristics of the shorter time apertures and the estimated respiration characteristics of the longer time apertures.

RELATED PATENT DOCUMENTS

This application is a divisional of U.S. patent application Ser. No.11/300,675 filed on Dec. 14, 2005, which is incorporated herein byreference in its entirety.

FIELD OF THE INVENTION

The present invention relates generally to respiration detection andmonitoring and, more particularly, to generating respiration metrics.

BACKGROUND OF THE INVENTION

The human body functions through a number of interdependentphysiological systems controlled through various mechanical, electrical,and chemical processes. The metabolic state of the body is constantlychanging. For example, as exercise level increases, the body consumesmore oxygen and gives off more carbon dioxide. The cardiac and pulmonarysystems maintain appropriate blood gas levels by making adjustments thatbring more oxygen into the system and dispel more carbon dioxide. Thecardiovascular system transports blood gases to and from the bodytissues. The respiratory system, through the breathing mechanism,performs the function of exchanging these gases with the externalenvironment. Together, the cardiac and respiratory systems form a largeranatomical and functional unit denoted the cardiopulmonary system.

Various disorders that affect the cardiovascular system may also impactrespiration. For example, heart failure is an abnormality of cardiacfunction that causes cardiac output to fall below a level adequate tomeet the metabolic demand of peripheral tissues. Heart failure isusually referred to as congestive heart failure (CHF) due to theaccompanying venous and pulmonary congestion. Congestive heart failuremay have a variety of underlying causes, including ischemic heartdisease (coronary artery disease), hypertension (high blood pressure),and diabetes, among others.

Various types of disordered respiration are associated with CHF. Forexample, rapid shallow breathing is one of the cardinal signs of heartfailure. The appearance of rapid, shallow breathing in a CHF patient isoften secondary to increased pulmonary edema, and can indicate aworsening of patient status. An abnormally high respiration rate thuscan be an indicator of CHF decompensation. It is estimated that nearlyone million hospital admissions for acute decompensated congestive heartfailure (CHF) occur in the United States each year, which is almostdouble the number admitted 15 years ago. The re-hospitalization ratesduring the 6 months following discharge are as much at 50%. Nearly 2% ofall hospital admissions in the United States are for decompensated CHFpatients, and heart failure is the most frequent cause ofhospitalization in patients older than 65 years. The average duration ofhospitalization is about 6 days. Despite aggressive therapies, hospitaladmissions for CHF continue to increase, reflecting the prevalence ofthis malady.

Because of the complex interactions between the cardiovascular,pulmonary, and other physiological systems, as well as the need forearly detection of various diseases and disorders, an effective approachto monitoring and early diagnosis is needed. Accurately characterizingpatient respiration aids in monitoring and diagnosingrespiration-related diseases or disorders. Evaluating patientrespiration information may allow an early intervention, preventingserious decompensation and hospitalization.

SUMMARY OF THE INVENTION

The present invention is directed to methods, devices, and systemsproviding respiration information. One embodiment is directed to amethod for providing respiration information. The method involvesgenerating a signal indicative of respiration. For each apertures of aplurality of shorter time apertures and for each aperture of a pluralityof longer time apertures an estimated characteristic of the respirationis determined based on the respiration signal. One or more respirationmetrics are determined using one or both of the estimated respirationcharacteristics of the plurality of shorter time apertures and theestimated respiration characteristics of the plurality of longer timeapertures. In some configurations, at least one of generating thesignal, determining the estimated characteristic, and determining theone or more respiration metrics is performed at least in partimplantably.

According to one implementation of the method, determining the estimatedrespiration characteristic for each aperture includes measuring arespiration characteristic for each breath cycle of the aperture. Theestimated respiration characteristic for the aperture is determinedbased on the measured respiration characteristics. For example, theestimated respiration characteristic for each of the apertures may bebased on a median value of the measured respiration characteristics.Determining the estimated respiration characteristic for each aperturemay involve determining an estimated respiration rate for each aperture.

The estimated respiration characteristic for each of the plurality ofshorter time apertures may be a maximum respiration rate for each of theplurality of shorter time apertures. The estimated respirationcharacteristic for each of the plurality of longer time apertures may bea minimum respiration rate for each of the plurality of longer timeapertures. The respiration metrics may be a daily maximum respirationrate determined using the maximum respiration rates of the plurality ofshorter time apertures and a daily minimum respiration rate determiningusing the minimum respiration rates of the plurality of longer timeapertures.

The method may also involve developing a trend using at least one of theestimated respiration characteristics determined for the plurality ofshorter time apertures, the estimated respiration characteristicsdetermined for the plurality of longer time apertures, and the one ormore respiration metrics.

The method may also involve detecting a presence of a disease ordisorder using at least one of the estimated respiration characteristicsdetermined for the plurality of shorter time apertures, the estimatedrespiration characteristics determined for the plurality of longer timeapertures, and the one or more respiration metrics. For example, thedisease or disorder detected may include heart failure and/or a symptomor heart failure. The method may include a progression of heart failureand/or a heart failure symptom using at least one of the estimatedrespiration characteristics determined for the plurality of shorter timeapertures, the estimated respiration characteristics determined for theplurality of longer time apertures, and the one or more respirationmetrics. A therapy may be initiated, modified or terminated based on theheart failure progression. According to one implementation, the therapyincludes a cardiac pacing therapy.

Another embodiment of the invention is directed to a respirationinformation device. The respiration information device includes timercircuitry configured to time a plurality of shorter time apertures and aplurality of longer time apertures. A respiration sensor, which may beimplemented as a transthoracic impedance sensor, is configured togenerate a signal indicative of patient respiration. Respirationinformation circuitry determines, for each aperture of the plurality ofshorter time apertures and for each aperture of the plurality of longertime apertures, an estimated characteristic of the respiration. Therespiration information circuitry may also be configured to determineone or more respiration metrics using one or both of the estimatedrespiration characteristics of the shorter time apertures and theestimated respiration characteristics of the longer time apertures. Insome embodiments, at least one of the timer circuitry, the respirationsensor, and the respiration information circuitry includes animplantable component.

In one implementation, the respiration information circuitry includesmeasurement circuitry configured to measure a respiration rate for eachbreath cycle of each aperture. A respiration processor is coupled to themeasurement circuitry and is configured to determine an estimatedrespiration rate for each aperture based on the measured respirationrates. For example, the respiration information circuitry may beconfigured to determine a maximum respiration rate from the estimatedrespiration rates of the plurality of shorter time apertures and todetermine a minimum respiration rate from the estimated respirationrates of the plurality of longer time apertures.

The respiration information device may further include a trending unitand/or a diagnostics unit. The trending unit is configured to develop atrend using at least one of the estimated respiration characteristicsdetermined for the plurality of shorter time apertures, the estimatedrespiration characteristics determined for the plurality of longer timeapertures, and the one or more respiration metrics. The diagnostics unitis configured to detect a presence of a disease or disorder, such asheart failure, using at least one of the estimated respirationcharacteristics determined for the plurality of shorter time apertures,the estimated respiration characteristics determined for the pluralityof longer time apertures, and the one or more respiration metrics.

The respiration information device may also include a therapy controlunit configure to control a therapy, such as a cardiac pacing therapy,based on a presence of a disease or disorder.

The above summary of the present invention is not intended to describeeach embodiment or every implementation of the present invention.Advantages and attainments, together with a more complete understandingof the invention, will become apparent and appreciated by referring tothe following detailed description and claims taken in conjunction withthe accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a flowchart illustrating the use of median estimators toderive respiration metrics in accordance with embodiments of theinvention;

FIG. 1B is a flowchart illustrating a method for generating and usingdaily respiration metrics in accordance with embodiments of theinvention;

FIG. 2 is a flowchart illustrating a method for determining respirationmetrics using longer duration apertures to determine a first respirationmetric and shorter duration apertures to determine a second respirationin accordance with embodiments of the invention;

FIG. 3 is a flowchart illustrating the use of overlapping apertures todetermine respiration metrics is in accordance with further embodimentsof the invention;

FIG. 4 is a flowchart illustrating a method for removing a predominanceof the erroneous breath detections in accordance with other embodimentsof the invention;

FIG. 5 illustrates a more detailed flowchart of a process for detectingspurious measurements caused by components of cardiac activity in therespiration waveform in accordance with embodiments of the invention;

FIGS. 6A and 6B illustrate an implementation for determining respirationmetrics including daily minimum respiration rate, daily maximumrespiration rate, and daily median respiration rate in accordance withan embodiment of the invention

FIG. 7 illustrates a medical device configured to estimatecharacteristics of a respiration signal and/or develop respirationmetrics and trends in accordance with embodiments of the presentinvention;

FIG. 8 is an illustration of an implantable medical device including asubcutaneous, non-intrathoracic lead assembly shown implanted outsidethe ribcage, the implantable medical device implemented to senserespiration of a patient for use in determining respiration metrics inaccordance with embodiments of the invention; and

FIG. 9 is a block diagram showing a variety of illustrative operationsthat may be performed based on measuring and/or estimating respirationcharacteristics that may be used to develop respiration metrics ortrends in accordance with embodiments of the invention.

While the invention is amenable to various modifications and alternativeforms, specifics thereof have been shown by way of example in thedrawings and will be described in detail below. It is to be understood,however, that the intention is not to limit the invention to theparticular embodiments described. On the contrary, the invention isintended to cover all modifications, equivalents, and alternativesfalling within the scope of the invention as defined by the appendedclaims.

DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS

In the following description of the illustrated embodiments, referencesare made to the accompanying drawings, which form a part hereof, and inwhich is shown by way of illustration, various embodiments in which theinvention may be practiced. It is to be understood that otherembodiments may be utilized, and structural and functional changes maybe made without departing from the scope of the present invention.

A wide variety of medical devices may be configured to quantify patientrespiration in accordance with the present invention. Such devices maybe configured with a variety of sensor arrangements for sensing patientrespiration, including external respiration sensors, implantableintrathoracic respiration sensors, such as transvenous, endocardial,and/or epicardial sensors (i.e., intrathoracic electrodes), and/orsubcutaneous, non-intrathoracic sensors, including can, header, andindifferent electrodes, and subcutaneous arrays or lead electrodes(i.e., non-intrathoracic electrodes). Quantification of patientrespiration may be implemented to estimate respiration characteristics,determine respiration metrics and/or develop trends based on therespiration characteristic and/or metrics. The respiration informationdeveloped by these devices may be used to develop a respiration trendbased on a patient's respiration rate distribution. Such devices arereferred to herein generally as a respiration sensing medical device(RSMD) for convenience.

Respiration rate has been shown to be predictive of mortality in a CHFpatient population. Symptoms of dyspnea are among the primary reasonsfor patients' reduced quality of life and are a primary reason why manyCHF patients return to the hospital during a CHF decompensation episode.When monitoring or diagnosing CHF patients, patient respiration rate isan important symptom. Respiration rate information yields knowledge ofhow long a patient stays dyspneic so as to relate to the worsening oftheir CHF disease state. When the patient spends more time at higherrespiration rates, this is indicative of a worsening of their CHFstatus.

As heart failure patients become acutely decompensated, they may presentwith tachypnea with abnormally elevated respiration rates of 25-30breaths per minute, even at rest. Even in the chronic, non-decompensatedstate, heart failure patients have elevated respiration rates. Theserates become even more highly elevated in associated withdecompensation. Thus, for many patients, respiration rate provides avaluable indication or prediction of impending acute decompensation ofcongestive heart failure. Information developed from respiratory ratedata in accordance with the present invention provides for enhancedmonitoring and therapy management of CHF patients, particularly when theCHF status of a patient is in decline.

Methodologies in accordance with the present invention advantageouslyprovide physicians with a quantified respiration metric and/or trendthat can be used to monitor a patient's changing CHF status andquantitatively evaluate the effectiveness of therapy (e.g., drug orcardiac stimulation therapy) delivered to the patient. The methodologiesused for developing respiration data involve measuring values of arespiration characteristic, which may be respiration rate, but couldalso be breath interval, tidal volume, and/or other respirationcharacteristics. The respiration characteristic measurements may be madefor one or more breath cycles, or each breath cycle during a pluralityof time apertures, which may or may not be overlapping in time. Anestimated respiration characteristic, e.g., estimated rate, breathinterval, tidal volume, etc, may be determined from the set of measuredcharacteristic values for a particular aperture to summarize themeasurements for the particular aperture. In one implementation, themedian value of the respiration characteristic measurements made duringan aperture is used to estimate the respiration characteristic of theaperture. Other statistical estimates (e.g., mean) or non-statisticalestimates (e.g., based on measured morphological characteristics of therespiration signal) may alternatively be used. The estimated respirationcharacteristics of a plurality of apertures may be used to develop arespiration trend, or may be used to derive a respiration metric thatspans a period of time, such as a daily minimum value or daily maximumvalue. The respiration metrics may also be trended. As applied herein,an estimated respiration characteristic is estimated based on themeasured respiration characteristic values of an individual aperture.Respiration metrics, such as daily respiration metrics, are determinedbased on the estimated respiration characteristics of a plurality ofapertures.

One implementation involves the use of a median estimator to determinedaily respiration rate metrics, such as maximum respiration rate over aperiod of time and/or daily minimum respiration rate over a period oftime. A daily median respiration rate may also be determined. Theminimum respiration rate may well be the most specific measure ofpatient respiratory distress. For example, if during the course of theday, the respiratory rate never drops below 18 breaths/minute, it mayindicate an abnormal rapid-shallow breathing pattern, even at rest. Thismay provide a valuable measure of patient respiratory status, includingrespiration mode changes associated with heart failure decompensation.

The daily maximum respiration rate may be best interpreted byconsidering it in association with the patient's daily activity. In ahealthy, active patient, the maximum respiration rate will besignificantly higher than the minimum value, and will vary considerablyfrom day to day, reflecting the variability in the patient's activities.If elevated maximum respiration rates are associated with periods ofvery limited activity, the patient may be experiencing exertionaldyspnea even at low levels of exertion (for example, simply walkingaround the house, or climbing the stairs), which may indicate worseningpatient status. On the other hand, a person whose activities areseverely limited by health conditions may show less of a spread fromminimum to maximum, and less day-to-day variability in maximumrespiration rate, due to limited, consistent daily activity patterns.

The median respiration rate is representative of the predominantrespiration rate for a given time period. The daily median is relativelyinsensitive to transiently elevated respiration rates during periods ofhigh activity, and also relatively insensitive to the lowest respirationrates typically occurring during deep sleep. The median correspondsclosely to the resting respiration rate a physician observes during aclinic visit.

In one embodiment, a patient's daily minimum respiration rate, dailymaximum respiration rate, and daily median respiration rate aredetermined. In this embodiment, the patient's respiration rate ismeasured for each breath cycle in a plurality of time apertures thatcover about a 24 hour period. The median respiration rate is estimatedfor each time aperture. The daily minimum respiration rate is determinedas the minimum median respiration rate of the time apertures spanningthe 24 hour period. The daily maximum respiration rate is determined asthe maximum median respiration rate of the time apertures spanning the24 hour period. In one implementation, the daily median respiration ratemay be determined as the median of the median respiration ratesestimated for all of the time apertures that span the 24 hour period. Inanother implementation, the daily median respiration rate may bedetermined as the median value of all the respiration rate valuesmeasured over the 24 hour period.

The use of median estimators to derive respiration metrics isillustrated in the flowchart of FIG. 1A. Patient respiration is sensedand a signal indicative of patient respiration is generated 101. Thepatient respiration signal may be generated, for example, by any of avariety of implantable or patient external sensors, such as animplantable transthoracic impedance sensor, external respiratory bandshaving piezoelectric or other sensor elements, a respiratory mask flowsensor, or other types of respiration sensors. A characteristic of therespiration signal, such as respiration rate per breath cycle, ismeasured 103 during each of a plurality of time apertures. The medianvalue of the respiration characteristic measurements for each apertureis determined 105. For example, if respiration rate is the measuredcharacteristic, the median value of the respiration rates measured foreach breath cycle during the aperture is determined. The median value isused to estimate the respiration rate of the aperture. One or morerespiration metrics are determined 107 based on the estimatedrespiration rates (i.e., median values) of the apertures.

In one embodiment, a method for generating and using daily respirationmetrics is illustrated in FIG. 1B. The process involves the use of animplantable transthoracic impedance sensor for determining a dailymaximum and/or daily minimum respiration metric based on medianestimators for the aperture respiration characteristics. In accordancewith this embodiment, a respiration signal is generated 102 by antransthoracic impedance sensor implemented in conjunction with animplantable cardiac rhythm management (CRM) device. The transthoracicimpedance sensor comprises intracardiac electrodes coupled to sensordrive/sense circuitry disposed within the CRM housing. The sensor drivecircuitry delivers an electrical excitation signal, such as a strobedsequence of current pulses or other measurement stimuli, across thethorax via one set of the intracardiac electrodes. In response to thedrive current, a response voltage is sensed by the sense circuitry usinganother set of the intracardiac electrodes. The response voltagerepresents the transthoracic (i.e., across a portion of the chest orthorax) impedance. Transthoracic impedance sensing provides a voltagesignal that tracks patient respiration and may be used to determine howfast and/or how deeply a patient is breathing. Additional aspects oftransthoracic impedance sensing that may be utilized in conjunction withvarious embodiments of the present invention are described in commonlyowned U.S. Pat. No. 6,076,015 which is incorporated herein by reference.

A plurality of time apertures, covering about a 24 hour period, aresuperimposed relative to the generated respiration signal. The breathintervals occurring in each aperture are measured 104 and respirationrates for each breath cycle are calculated as the inverse of eachmeasured breath interval. A histogram of the measured respiration ratesis developed 106. The median value of the measured respiration ratesdetermined from the histogram is computed and stored 108. Median valuesfor each of the apertures are stored 109 throughout the 24 hour period.The maximum of the median values is selected 110 as the maximum dailyrespiration rate. The minimum of the median values is selected 111 asthe minimum daily respiration rate. The daily minimum and maximumrespiration rates may optionally be telemetered 112 to a remote device,and/or stored or used 113 to develop trend data within the CRM device orremote device. The daily minimum and/or maximum respiration rates, ortrend data developed from the daily metrics, may optionally be displayed114 on the device programmer screen or other user interface device asindividual daily respiration metrics or as trended data. The dailymaximum and/or minimum respiration rates or trends of these rates may beused 115 for disease diagnosis and/or to track the progression ofdisease symptoms and/or to control therapy. Although this exampledescribes the use of daily metrics, other periodic metrics may also bedetermined, such as weekly metrics, bi-weekly metrics, or monthlymetrics. In addition, metrics other than maximum and minimum respirationrates may be determined, such as the daily, weekly, monthly, etc.,median or mean respiration rates.

The use of median estimators provides a robust determination of thedaily respiration metrics. Breath detection errors may cause extremevalues in the breath interval stream which show up as extreme measuredrespiration rate values in the distribution. The median is inherentlyless sensitive to extreme values on the tail of the distribution thanthe mean. Even without detection errors, the breath intervals themselvesoften form a skewed distribution due to variable respiration patternswithin the aperture, such that the median is a more appropriate measureof the central tendency of the respiration intervals within an aperture.While other respiration statistics, such as the mean value, may be used,the median typically provides estimates more representative of thepredominant respiration rate for a time aperture than the mean. This islargely due to the frequently asymmetric respiration intervalhistograms, which may have long “tails” that corrupt the mean estimator.Furthermore, the median lends itself to simple, efficient computation interms of interval histograms.

In some embodiments, time apertures used to determine one respirationmetric may have a different duration than the time apertures used todetermine another respiration metric. The duration of the time aperturerequired to accurately estimate a particular respiration characteristicbased on measurements taken within the aperture is related to thefrequency of occurrence of the respiration characteristic used todevelop the estimate. A statistically stable, consistent estimaterequires a sufficiently long observation aperture. Stability of arespiration characteristic estimate improves with increasing apertureduration which allows a corresponding increase in the number ofrespiration cycles over which to compute the estimated characteristic.Selection of time aperture duration involves a trade-off between thestability of the estimate and the desire to capture transient,relatively short-term changes in respiration characteristics, due toexercise, for example, or other short-term factors.

The flowchart of FIG. 2 illustrates a method for determining respirationmetrics using longer duration apertures to determine a first respirationmetric and shorter duration apertures to determine a second respirationmetric. The example provided in FIG. 2 involves two sets of apertures ofdifferent durations which are used to determine first and secondrespiration metrics, although this process could be extended to anynumber of aperture sets and respiration metrics.

Patient respiration is sensed 201 and a signal indicative of respirationis generated. Respiration signal characteristic values are measured 202during each aperture in two sets of time apertures, denoted first andsecond time apertures, where the apertures of the first set have alonger duration than apertures of the second set. An estimatedrespiration characteristic for the aperture is estimated 203 from themeasured respiration characteristic values for each long aperture andfor each short aperture. The estimated respiration characteristics ofthe first (long) apertures are used to determine 205 a first respirationmetric. The estimated respiration characteristics determined for thesecond (short) apertures are used to determine 207 a second respirationmetric.

The processes illustrated by FIG. 2 may be used in developing dailymaximum and minimum respiration rate metrics, for example. Ideally, toaccurately estimate peak respiration rates, the time aperture should beof a similar duration to the shortest duration episode which is expectedto significantly affect the respiration rate estimate for the aperture,so long as this aperture contains enough breaths to provide a reliableestimate of respiration rate. Thus, time apertures used to determine thedaily minimum respiration rate may be longer than the time aperturesused to determine the daily maximum respiration rate. Because theconditions producing the daily minimum rate, such as sleep, typicallylast on the order of hours, longer apertures tend to produce quitestable, consistent estimates of the minimum respiration rate metricdetermined from a number of apertures. In one implementation, longerduration apertures of about 30 minutes may be used to determine thedaily minimum respiration metric. At an average resting respiration rateof 15 breaths/minute, there will be an average of 450 breaths per thirtyminute aperture. A 30 minute aperture duration will provide goodperformance for very low respiration rates, providing 120 breaths withinthe thirty minute aperture on which to base the estimate at arespiration rate of 4 breaths/minute, which is selected as a minimumrespiration rate limit in some embodiments. Respiration rates that fallbelow the minimum respiration rate limit may be discarded and neverenter into the computation of respiration metrics or trends.

Conditions producing the daily maximum rate are typically short induration (e.g. exercise lasting from about 5-60 minutes). Thus, using anunnecessarily long time aperture in estimating the daily maximum ratewill lead to underestimation of the peaks, since the breaths within theaperture will be a mixture of those from exercising and restingconditions. For the daily maximum respiration rate metric, the desire toaccurately capture relatively short-term changes in respiration rate dueto short duration activities of daily living places differentrequirements on the aperture length.

While it is still desired to have a sufficient number of breaths onwhich to form a reliable estimate, it is also beneficial to have a shortduration aperture so that relatively brief elevations in rate are moreaccurately estimated. For this reason, a shorter aperture is ideallyused in the algorithm to compute the daily maximum rate metrics. Sincethis aperture will be used only for computation of daily maximum rates,there is less concern that the aperture be long enough to provide enoughbreaths at the lower extremes of respiration rate, e.g. at about 4breaths/minute. An aperture duration of about 10 minutes may be chosenfor computing the daily maximum respiration rate metrics. This apertureduration will provide good performance for elevated respiration rateswith a duration of as low as 5 minutes or less, and for normalrespiration rates (even those as low as 10 breaths/minute) will stillprovide at least 100 breaths within the aperture on which to base theestimate. In some embodiments, a maximum respiration rate is used. Forexample, the maximum respiration rate may be about 65 breaths/minute.Respiration rates beyond the maximum respiration rate limit may bediscarded and never enter into the computation of respiration metrics ortrends.

The median value provides a robust estimate of the respirationcharacteristics of an aperture as long as the sample size is reasonablylarge. Accordingly, it is natural to require that the median value of arespiration characteristic, such as respiration rate, be determinedbased on a minimum number of values measured in the aperture. Typically,there should be on the order of about 100 or more samples in thedistribution. Thus, even for the lowest allowable respiration rate, a 30minute aperture contains a sufficient number of breath intervals to forma reasonable estimate of the respiration rate median.

Due to the possibility of missed detections and/or periods of nobreathing (apnea), the situation may arise that a respirationcharacteristic may be estimated using a small number of breathintervals. In order to protect against the possibility of reporting arespiration characteristic of an aperture based on a undesirably smallnumber of respiratory cycles, any characteristic derived using too fewbreaths may be marked as invalid, and not be used to develop the dailyrespiration metrics or trends.

Further, due to potential respiration sensor malfunctions, orsensitivity issues, it is conceivable that estimates of a respirationcharacteristic, such as respiration rate, will be unavailable for asignificant portion of the day. If respiration rate estimates areunavailable for too much of the day, then the validity of therespiration metrics, e.g., minimum rate, maximum rate, median rate forthat period may be compromised. For example, if less than 18 hours ofvalid respiration rate estimates exist for a given day, the respirationmetrics and/or trend values for that day may be declared invalid, andnot be presented to the end user.

Some embodiments of the invention involve generating respiration signalsin apertures which are overlapping in time. The use of overlappingapertures reduces the potential of misestimating the respirationcharacteristic of an aperture due to a period of temporarily changedcharacteristics. For example, with respect to respiration rate, evenwith aperture widths selected to enhance respiration rate characteristicestimation as described above, the potential exists for misestimating anaperture's respiratory rate if a period of elevated or depressedrespiratory rate falls on the border between two adjacent timeapertures. This will result in two consecutive apertures in which therespiration contains a mixture of “slow” and “fast” intervals, leadingto a widened (potentially bimodal) distribution of intervals. Therespiration rate estimate is likely to fall short of the respiratoryrate excursion, and will likely report a “compromise” respiration rateestimate. In order to ensure that the estimated aperture respirationrates are not erroneous due to this aperture edge effect, it isadvantageous to overlap the apertures by a certain amount, such as about50%. In this configuration, if an event is right on the edge of twoadjacent apertures, it will fall in the center of the overlappedaperture.

The use of overlapping apertures to determine respiration metrics isillustrated in the flowchart of FIG. 3. Patient respiration is sensedand a respiration signal is generated 310. A respiration characteristic,e.g., respiration rate, is estimated 312 for each overlapping aperturebased on measured rates for each breath cycle of the respiration signal.A respiration metric is determined 314 based on the estimatedrespiration characteristics of a plurality of apertures. For example,daily respiration metrics, such as a daily maximum respiration rate ordaily minimum respiration rate, may be determined based on estimatedrespiration rate characteristics of a plurality of apertures that coverabout a 24 hour period.

As previously discussed, estimation of respiration rate for eachaperture may be performed using breath cycles that fall within a minimumrate limit or maximum rate limit. Breath cycles that are beyond theminimum or maximum rate limit may be discarded, and not used to estimatethe respiration rate characteristic for the apertures, to determine therespiration rate metrics, or to develop trends based on the respirationrate characteristics or respiration rate metrics.

In accordance with some embodiments, the respiration signal used toestimate the respiration characteristics may be the signal generated bya transthoracic impedance sensor of an implantable rate adaptivepacemaker. The transthoracic impedance signal typically has beenfiltered by the sensor circuitry to remove components of cardiacactivity and other noise from the signal. However, particularly forpatients with highly unstable heart rates, such as occur with atrialfibrillation, the filtering designed to remove the cardiac activitycomponent from the transthoracic impedance signal is not alwayscompletely effective. At times there may be a considerable amount ofcardiac activity component left in the waveform after filtering. Theseartifacts can cause a significant number of false breath detectionsleading to erroneously high estimates of respiration rate.

In accordance with some embodiments of the invention, a “breath pruning”process is implemented to remove a predominance of the erroneous breathdetections, such as those triggered by cardiac activity. The process isillustrated by the flowchart of FIG. 4. A signal indicative of patientrespiration is generated 410. Breaths are detected 420 from therespiration signal. Spurious breath detections associated with cardiacactivity are identified 430. An estimated respiration characteristic isdetermined 440 based on the detected breaths excluding the spuriousbreath detections.

FIG. 5 illustrates a more detailed flowchart of a process foridentifying spurious breath detections caused by components of cardiacactivity in the respiration waveform. The process illustrated in FIG. 5compares breath intervals to a multiple of a cardiac R-R intervalestimate to determine whether a breath detection should be used todetermine a breath interval and to calculate breath rate. The systemwaits 505 for a new R-R interval which may be detected, for example,using a cardiac electrogram signal. If a new R-R interval is detected510, the detected R-R interval is used to update 515 a filtered R-Restimate (RR_(est)(n)). In one embodiment, the updated R-R estimate,RR_(est)(n), may be expressed as follows:RR _(est)(n)=31/32*RR _(est)(n−1)+1/32*RR(n)  [1]

where RR(n) is the current detected R-R interval and RR_(est)(n−1) isthe previous filtered R-R estimate.

The system waits 520 for a new breath detection. If a new breath isdetected 525, a breath interval is computed 530 by subtracting the lastprevious valid breath time from the new breath time.

The breath interval is compared 535 to a multiple of the most recentlyupdated filtered R-R interval estimate, RR_(est)(n). If the breathinterval is 540 less than the R-R interval estimate, RR_(est)(n),multiplied by a coefficient, such as about 2.15, for example, the newbreath detection is discarded 545 and the breath interval computed basedon the discarded breath detection is not used to calculate a breathrate. If the breath interval is 540 greater than or equal to RR_(est)(n)multiplied by the coefficient, then the breath rate is computed 550 forthe breath interval. For example, the breath rate may be calculated fromthe breath interval in breaths per minute as follows:Breath Rate=60/Breath Interval,  [2]

where Breath Interval is in units of seconds.

As previously discussed, the breath rates of each breath in an aperturemay be used to estimate the breath rate for the aperture. In oneimplementation, the characteristic breath rate for the aperture isestimated using the median value of all the breath rates measured in theaperture.

FIGS. 6A and 6B illustrate an implementation for determining respirationmetrics including daily minimum respiration rate, daily maximumrespiration rate, and daily median respiration rate in accordance withan embodiment of the invention. Patient respiration is sensed and arespiration signal is generated. Overlapping apertures, as illustratedin FIG. 6A, are superimposed on the respiration signal. The aperturesinclude a 24 hour aperture 605 which is used to determine a daily medianrespiration rate. The apertures also include 10 minute aligned apertures610 and 10 minute offset apertures 615. The 10 minute offset apertures615 are offset from the 10 minute aligned apertures 610 by 50%. The 10minute aligned and offset apertures 610, 615 are used to determine adaily maximum respiration rate. The overlapping apertures also include30 minute aligned apertures 620 and 30 minute offset apertures 625. The30 minute offset apertures 625 are offset from the 30 minute alignedapertures 620 by 50%. The 30 minute aligned and offset apertures 620,625 are used to determine a daily maximum respiration rate.

Breath rates for each respiration cycle are measured and are used toupdate histograms corresponding to each aperture. In the implementationillustrated in FIGS. 6A and 6B, five concurrently running histograms areused, a 10 minute aligned histogram, a 10 minute offset histogram, a 30minute aligned histogram, a 30 minute offset histogram, and a 24 hourhistogram. A median respiration rate value is determined from eachhistogram. The daily minimum rate is determined from the median valuesof the 30 minute aligned and offset histograms that span a 24 hourperiod. The daily maximum rate is determined from the median values ofthe 10 minute aligned and offset histograms that span the 24 hourperiod. The daily median rate is the median value of the 24 hourhistogram. A process 600 for determining these daily metrics inaccordance with one embodiment is illustrated in FIG. 6B.

Breath rates are measured 630 from the respiration signal and used toupdate the five concurrently running histograms. The respiration signalmay be generated, for example, by a transthoracic impedance sensorsignal implemented in an implantable device. Breath detections receivedfrom the sensor may be pre-processed as described, for example, inconnection with FIGS. 4 and 5, to avoid the use of spurious breathdetections in determining the respiration metrics or trends. The process600 may require that the breath rates meet certain criteria. In additionto providing breath rates for use in the respiration metric process 600,the respiration sensor circuitry, e.g., transthoracic impedance sensor,may provide data quality/status flags. Flags produced by the impedancesensor noise detection hardware/software may be used by the respirationmetric process 600 to avoid using potentially corrupted data flagged astoo noisy by the sensor. Further, the breath rates used to update thehistograms may be constrained to fall within a certain range of breathrates, e.g., about 4 breaths/minute to about 65 breaths/minute.

A histogram bin for a measured breath rate is determined 632. Each ofthe concurrently running histograms is updated 641-645 based on themeasured breath rate. In some implementations, the breath rates may becomputed in breaths/minute and the spacing of the histogram bins is 1breath/minute. After an aperture is concluded 651-655, the median ratevalue for the aperture is computed 661-665. If an insufficient number ofbreaths are detected during an aperture, e.g., fewer than 100 breaths,then the aperture may be labeled invalid and a median for that aperturemay not be computed. Throughout the 24 hour period, the running maximumof the median rate values for the 10 minute apertures is retained 671and the running minimum of the median rate values for the 30 minuteapertures is retained 672. After the 24 hour period is concluded 681,682, the daily maximum rate is reported 691, and the daily minimum rateis reported 692. The daily median respiration rate is determined 665 asthe median rate value of the 24 hour aperture and reported 693. Thedaily maximum, minimum, and median values may be stored, telemetered toa remote device, displayed on a display, or otherwise accessed by aphysician or others. The daily minimum, maximum and median rates may benumerically displayed. A respiration rate trend of one or more of theminimum, maximum, or median rates may be developed that spans a numberof days and may also be displayed.

Various embodiments described herein may be used in connection withdevices that provide for CHF monitoring, diagnosis, and/or therapy. Arespiration sensing medical device (RSMD) of the present invention mayprovide CHF therapy features involving dual-chamber or bi-ventricularpacing/therapy, cardiac resynchronization therapy, cardiac functionoptimization, drug therapy, respiration therapy and/or other CHF relatedmethodologies. For example, an RSMD of the present invention mayincorporate features of one or more of the following references:commonly owned U.S. patent application Ser. No. 10/270,035, filed Oct.11, 2002, entitled “Timing Cycles for Synchronized Multisite CardiacPacing;” and U.S. Pat. Nos. 6,411,848; 6,285,907; 4,928,688; 6,459,929;5,334,222; 6,026,320; 6,371,922; 6,597,951; 6,424,865; and 6,542,775,each of which is hereby incorporated herein by reference.

The respiration metrics and/or trends developed as described in variousembodiments herein may be used in a number of ways to assist in thediagnosis and/or treatment of patients suffering from CHF or otherrespiratory or cardiopulmonary disorders. According to one aspect of theinvention, the respiration information may be presented to a patient'sphysician for use in making diagnosis and/or therapy decisions. In oneimplementation, respiration information acquired by the RSMD, e.g.,respiration characteristics (estimated or measured values), respirationmetrics, and/or trends of respiration characteristics and/or metrics,may be presented for viewing on demand by the physician via a display ona device programmer or other remote device. The physician may use therespiration information to diagnose the patient and/or to initiate,terminate or modify therapy delivered to the patient. In someimplementations, an implantable RSMD may communicate wirelessly with aremote device to download respiration information periodically so thatcurrent respiration information is available to the physician.

According to another aspect, the respiration information may be used bythe RSMD to automatically make a diagnosis or to automatically controltherapy. The RSMD may compare the respiration metrics and/or trendsdeveloped as described in the various embodiments, to one or morethresholds. The RSMD may detect or diagnose the presence of adisease/disorder, may determine the progression or regression ofdisease/disorder symptoms, and/or may determine if therapy should bemodified based on the comparison. The respiration information may beused alone, or may be combined with other information related to thedisease/disorder of concern. For example, the respiration informationmay be used in conjunction with additional sensed information and mayalso be used in conjunction with patient historical information orpatient input information, such as patient weight, or drug useinformation.

In one implementation, the RSMD may acquire information related topatient posture, cardiac functioning, and/or patient activity along withdeveloping the respiration metrics and/or trends described herein. TheRSMD may use the acquired posture, cardiac and/or activity informationin combination with the respiration metrics and/or trends to enhancediagnosis or therapy. For example, the RSMD may compare patient posture,cardiac functioning, activity, and respiration rate, respectively, tothresholds associated with each of these variables. In another example,the RSMD may combine the posture, cardiac functioning, activity andrespiration information via a weighted sum, for example. The combinedinformation may be compared to a single threshold to facilitatediagnosis and/or to determine the progression of disease symptoms and/orto indicate if therapy modification is appropriate.

If the RSMD automatically generates a diagnosis, the diagnosis may beprovided on demand, or in the form of an automatic alert generated whenpatient conditions indicate that the patient symptoms have deterioratedbeyond a trigger level. If the RSMD automatically initiates, terminates,or modifies therapy, the RSMD may develop a control signal transmittedto one or more therapy devices indicating the therapy change. Thecontrol signal may be generated by the RSMD based on the respirationinformation and/or additional information. For example, if the RSMD isused in conjunction with a CRM device, the control signal may controlmodification of various pacing parameters. In such an implementation,the therapy modification may include changing the pacing mode, e.g.,switching pacing from single ventricular pacing to bi-ventricularpacing, changing the pacing site, changing pacing rate, and/or modifyingvarious pacing delays such as the atrioventricular pacing delay and/orthe interventricular pacing delay. In another example, if the RSMD isused in conjunction with an implantable drug delivery device, such as adrug pump, the RSMD may automatically modify the type and/or titrationof drugs used to treat the patient's disease/disorder. Alternatively,the RSMD may inform the patient that their medication should be changed.The automatic therapy modification may be remotely reviewed and approvedby the patient's physician prior to making or suggesting themodification.

Certain configurations illustrated herein are generally described ascapable of implementing various functions traditionally performed by animplantable cardioverter/defibrillator (ICD), and may operate innumerous cardioversion/defibrillation modes as are known in the art.Examples of ICD circuitry, structures and functionality, aspects ofwhich may be used in a RSMD of the present invention, are disclosed incommonly owned U.S. Pat. Nos. 5,133,353; 5,179,945; 5,314,459;5,318,597; 5,620,466; and 5,662,688, which are hereby incorporatedherein by reference.

In particular configurations, systems and methods may perform functionstraditionally performed by pacemakers, such as providing various pacingtherapies as are known in the art, in addition tocardioversion/defibrillation therapies. Examples of pacemaker circuitry,structures and functionality, aspects of which may be incorporated in aRSMD of the present invention, are disclosed in commonly owned U.S. Pat.Nos. 4,562,841; 5,284,136; 5,376,106; 5,036,849; 5,540,727; 5,836,987;6,044,298; and 6,055,454, which are hereby incorporated herein byreference. It is understood that RSMD configurations may provide fornon-physiologic pacing support in addition to, or to the exclusion of,bradycardia and/or anti-tachycardia pacing therapies.

A RSMD in accordance with the present invention may implement diagnosticand/or monitoring functions as well as provide cardiac stimulationtherapy. Examples of cardiac monitoring circuitry, structures andfunctionality, aspects of which may be incorporated in a RSMD of thepresent invention, are disclosed in commonly owned U.S. Pat. Nos.5,313,953; 5,388,578; and 5,411,031, which are hereby incorporatedherein by reference.

Referring now to FIG. 7, there is illustrated an embodiment of a medicaldevice configured to estimate characteristics of a respiration signaland/or develop respiration metrics and trends in accordance withembodiments of the present invention. In this illustrative example, themedical device comprises a cardiac rhythm management (CRM) device 700including an implantable pulse generator 705 electrically and physicallycoupled to an intracardiac lead system 710.

Portions of the intracardiac lead system 710 are inserted into thepatient's heart 790. The intracardiac lead system 710 includes one ormore electrodes and/or sensors configured to sense electrical cardiacactivity of the heart, deliver electrical stimulation to the heart,sense transthoracic impedance, sense blood (internal filling) pressure,flow, and/or temperature, sense acceleration and/or body acoustics,and/or sense other physiological parameters of interest. Portions of thehousing 701 of the pulse generator 705 may optionally serve as a canelectrode.

Communications circuitry is disposed within the housing 701 forfacilitating communication between the pulse generator 705 and anexternal communication device, such as a portable or bed-sidecommunication station, patient-carried/worn communication station (e.g.,communicator), external programmer or advanced patient management systeminterface, for example. The communications circuitry may also facilitateunidirectional or bidirectional communication with one or moreimplanted, external, cutaneous, or subcutaneous physiologic ornon-physiologic sensors, patient-input devices and/or informationsystems.

The pulse generator 705 may optionally incorporate a motion detector 720that may be used to sense patient activity as well as variousrespiration and cardiac related conditions. For example, the motiondetector 720 may be optionally configured to sense snoring, activitylevel, and/or chest wall movements associated with respiratory effort,for example. The motion detector 720 may be implemented as anaccelerometer positioned in or on the housing 701 of the pulse generator705. For a motion sensor implemented as an accelerometer, the motionsensor may also provide respiratory, e.g. rales, coughing, and cardiac,e.g. S1-S4 heart sounds, murmurs, and other acoustic information. Anaccelerometer may be used to sense patient activity information whichmay be used in conjunction with respiration information.

The lead system 710 and pulse generator 705 of the CRM 700 mayincorporate one or more transthoracic impedance sensors that may be usedto acquire the patient's respiration waveform, or otherrespiration-related information. The transthoracic impedance sensor mayinclude, for example, one or more intracardiac electrodes 741, 742,751-755, 763 positioned in one or more chambers of the heart 790. Theintracardiac electrodes 741, 742, 751-755, 763 may be coupled toimpedance drive/sense circuitry 730 positioned within the housing of thepulse generator 705.

In one implementation, impedance drive/sense circuitry 730 generates acurrent that flows through the tissue between an impedance driveelectrode 751 and a can electrode on the housing 701 of the pulsegenerator 705. The voltage at an impedance sense electrode 752 relativeto the can electrode changes as the patient's transthoracic impedancechanges. The voltage signal developed between the impedance senseelectrode 752 and the can electrode is detected by the impedance sensecircuitry 730. Other locations and/or combinations of impedance senseand drive electrodes are also possible.

The lead system 710 may include one or more cardiac pace/senseelectrodes 751-755 positioned in, on, or about one or more heartchambers for sensing electrical signals from the patient's heart 790and/or delivering pacing pulses to the heart 790. The intracardiacsense/pace electrodes 751-755, such as those illustrated in FIG. 7, maybe used to sense and/or pace one or more chambers of the heart,including the left ventricle, the right ventricle, the left atriumand/or the right atrium. The lead system 710 may include one or moredefibrillation electrodes 741, 742 for deliveringdefibrillation/cardioversion shocks to the heart.

The lead system 710 may include one or more leads each having one ormore electrodes that extend into the heart. FIG. 7 shows three suchleads, one that extends into the right atrium, one that extends into theright ventricle, and one that extends into a coronary vein for placementat the surface of the left ventricle. The left ventricular lead, inparticular, includes an LV distal electrode 755 and an LV proximalelectrode 754 located at appropriate locations in or about the leftventricle for pacing and/or sensing the left ventricle. The leftventricular lead may be guided into the right atrium of the heart viathe superior vena cava. From the right atrium, the left ventricular leadmay be deployed into the coronary sinus ostium, the opening of thecoronary sinus. The lead may be guided through the coronary sinus to acoronary vein of the left ventricle. This vein is used as an accesspathway for leads to reach the surfaces of the left ventricle that arenot directly accessible from the right side of the heart.

The pulse generator 705 may include circuitry for detecting cardiacarrhythmias and/or for controlling pacing or defibrillation therapy inthe form of electrical stimulation pulses or shocks delivered to theheart through the lead system 710. The pulse generator 705 may alsoincorporate circuitry, structures and functionality of the implantablemedical devices disclosed in commonly owned U.S. Pat. Nos. 5,203,348;5,230,337; 5,360,442; 5,366,496; 5,397,342; 5,391,200; 5,545,202;5,603,732; and 5,916,243; 6,360,127; 6,597,951; and US PatentPublication No. 2002/0143264, which are hereby incorporated herein byreference.

For purposes of illustration, and not of limitation, various embodimentsof devices implemented in accordance with the present invention aredescribed herein in the context of RSMDs that may be implanted under theskin in the chest region of a patient. An RSMD may, for example, beimplanted subcutaneously such that all or selected elements of thedevice are positioned on the patient's front, back, side, or other bodylocations suitable for sensing cardiac activity and/or deliveringcardiac stimulation therapy. It is understood that elements of the RSMDmay be located at several different body locations, such as in thechest, abdominal, or subclavian region with electrode elementsrespectively positioned at different regions near, around, in, or on theheart.

The primary housing (e.g., the active or non-active can) of the RSMD,for example, may be configured for positioning outside of the rib cageat an intercostal or subcostal location, within the abdomen, or in theupper chest region (e.g., subclavian location, such as above the thirdrib). In one implementation, one or more leads incorporating electrodesmay be located in direct contact with the heart, great vessel orcoronary vasculature, such as via one or more leads implanted by use ofconventional transvenous delivery approaches. In another implementation,one or more electrodes may be located on the primary housing and/or atother locations about, but not in direct contact with the heart, greatvessel or coronary vasculature.

In a further implementation, for example, one or more electrodesubsystems or electrode arrays may be used to sense cardiac activity anddeliver cardiac stimulation energy in a RSMD configuration employing anactive can or a configuration employing a non-active can. Electrodes maybe situated at anterior and/or posterior locations relative to theheart. Examples of useful electrode locations and features that may beemployed in various embodiments of the present invention are describedin commonly owned, co-pending U.S. patent application Ser. Nos.10/465,520 filed Jun. 19, 2003, entitled “Methods and Systems InvolvingSubcutaneous Electrode Positioning Relative to a Heart,” and 10/738,608filed Dec. 17, 2003, entitled “Noise Canceling Cardiac Electrodes,”which are hereby incorporated herein by reference.

In one configuration, as is illustrated in FIG. 8, electrode subsystemsof a RSMD system are arranged about a patient's heart 810. The RSMDsystem includes a first electrode subsystem, comprising a can electrode802, and a second electrode subsystem 804 that includes at least twoelectrodes or at least one multi-element electrode. The second electrodesubsystem 804 may include a number of electrodes used for sensing and/orelectrical stimulation.

In various configurations, the second electrode subsystem 804 mayinclude a combination of electrodes. The combination of electrodes ofthe second electrode subsystem 804 may include coil electrodes, tipelectrodes, ring electrodes, multi-element coils, spiral coils, spiralcoils mounted on non-conductive backing, screen patch electrodes, andother electrode configurations as will be described below. A suitablenon-conductive backing material is silicone rubber, for example.

The can electrode 802 is positioned on the housing 801 that encloses theRSMD electronics. The RSMD system shown in FIG. 8 incorporates one ormore sensors configured to sense respiration. A sensing element, e.g.,electrode, used for respiration sensing may be disposed on housing 801,such that element 802 may be representative of such electrode(s) aloneor in combination with a can electrode. Sensing elements used forrespiration sensing may be disposed on another component of the RSMDsystem, such as on lead 806, a lead separate from lead 806, or on thesubsystem element 804, which may be representative of such sensingelement(s) alone or in combination with a cardiac electrode.

A RSMD of the present invention may be implemented to communicate with apatient management server or network via an appropriate communicationsinterface or an external programmer. A RSMD of the present invention maybe used within the structure of an APM system. The advanced patientmanagement system allows physicians to remotely and automaticallymonitor cardiac and respiratory functions, as well as other patientconditions.

In one example, a RSMD implemented as a cardiac pacemaker,defibrillator, or resynchronization device may be equipped with varioustelecommunications and information technologies that enable real-timedata collection, diagnosis, and treatment of the patient. Various RSMDembodiments described herein may be used in connection with advancedpatient management. Methods, structures, and/or techniques describedherein, which may be adapted to provide for remote patient/devicemonitoring, diagnosis, therapy, or other APM related methodologies, mayincorporate features of one or more of the following references: U.S.Pat. Nos. 6,221,011; 6,270,457; 6,277,072; 6,280,380; 6,312,378;6,336,903; 6,358,203; 6,368,284; 6,398,728; and 6,440,066, which arehereby incorporated herein by reference.

The components, functionality, and structural configurations depictedherein are intended to provide an understanding of various features andcombination of features that may be incorporated in a RSMD. It isunderstood that a wide variety of RSMDs and other implantable cardiacmonitoring and/or stimulation device configurations are contemplated,ranging from relatively sophisticated to relatively simple designs. Assuch, particular RSMD or cardiac monitoring and/or stimulation deviceconfigurations may include particular features as described herein,while other such device configurations may exclude particular featuresdescribed herein.

FIG. 9 illustrates a block diagram of a system 900 suitable forimplementing the methods of the invention as illustrated, for example,by the processes of FIGS. 1-6. In some embodiments, circuitry forestimating characteristics of patient respiration, determiningrespiration metrics and/or developing respiration trends is disposedwithin the housing of an implantable cardiac rhythm device 960. Thecardiac rhythm device 960 includes a cardiac lead system 910 that iselectrically coupled to the patient's heart. Electrical signals from thepatient's heart are sensed via the lead system 910 by cardiac sensingcircuitry 925. The cardiac therapy control circuitry 954 may detectarrhythmic conditions, such as bradyarrhythmia or tachyarrhythmia, basedon the sensed cardiac electrical signals. Cardiac therapy controlcircuitry 954 controls cardiac therapy circuitry 915 which generateselectrical stimulation pulses delivered to the heart via the lead system910 to treat various heart rhythm irregularities. For example, thecardiac therapy circuitry 914 may generate a series of low energyelectrical pacing pulses timed to assist the heart in maintaining ahemodynamically appropriate rhythm. The cardiac therapy circuitry 914may generate high energy shocks delivered to the heart if the cardiaccontrol circuitry 954 detects tachycardia or fibrillation, arrhythmicconditions producing a heart rate that is too fast and possibly lethal.

The system 900 includes a sensor 922 for sensing patient respiration.The sensor may be configured, for example, as intracardiac electrodesused to develop a transthoracic impedance signal which tracksrespiration. Respiration sensor drive circuitry 924 provides thenecessary drive signals to activate the drive electrodes 922. Responsesignals are sensed via sense electrodes 922 and are conditioned by therespiration sense circuitry 924.

The respiration drive/sense circuitry 924 generates a respiration signalthat is received by the respiration characteristic measurement circuitry921. The measurement circuitry 921 measures one or more characteristicsof the respiration signal. In various embodiments, the characteristicmeasured may comprise, for example, breath rate, breath interval, tidalvolume, or other respiration characteristics. A respirationcharacteristic may be measured for each breath cycle, e.g., breath rateper cycle or breath interval duration per cycle, or multiple breathcycles may be used in the respiration characteristic measurement, e.g.,average tidal volume for X number of breath cycles.

The measurement circuitry 921 may pre-process the respiration signalreceived from the respiration drive/sense circuitry 924 to removespurious breath detections, for example, as described in connection withFIGS. 4 and 5. In one scenario, the cardiac therapy control processor954 provides R-R interval information to the measurement circuitry 921.The measurement circuitry 921 compares breath intervals to filtered R-Rinterval estimates to identify and remove erroneous breath detectionsthat are due to cardiac activity as previously described.

A respiration processor 920 receives the measurements and uses themeasurements to estimate characteristics of the patient respiration. Thepatient respiration characteristics are estimated with respect toapertures timed by the aperture timing circuitry 923. For example, inone implementation, the measurement circuitry 921 measures a respirationrate for each breath cycle. The respiration processor 920 estimates acharacteristic of the patient respiration for each aperture. In someembodiments, the respiration processor 920 may form a histogram ofmeasured respiration rates received from the measurement circuitry 921and estimate the respiration rate of the aperture as the medianrespiration rate determined from the aperture histogram. The respirationrates for each aperture may be stored in memory 945, or may betransmitted via communications circuitry 935 to a remote device 965.

The respiration processor 920 may estimate respiration characteristicsfor consecutive and/or overlapping apertures. In some implementations,aperture durations may be selected based on the particular respirationcharacteristic being estimated. Respiration characteristic estimates ofthe apertures may be used to determine respiration metrics associatedwith a number of apertures spanning a period of time. For example, dailyminimum and maximum respiration rates, or other daily metrics may bedetermined for apertures spanning a 24 hour period. The respirationprocessor, in conjunction with the memory, may form a trend of themeasured respiration characteristics, the respiration characteristicestimates, the respiration metrics, and/or other respirationinformation. The respiration metrics and/or trends developed by therespiration processor 920 may be used by a diagnostics unit 955 to trackthe presence and/or progression of a disease, such as heart failure. Therespiration metrics and/or trends developed by the respiration processor920 may be transmitted to a remote device 965 via the communicationscircuitry 935. The respiration processor 920 may generate a controlsignal to control the cardiac therapy. For example, the cardiac therapycontrol unit 954 may modify a pacing therapy delivered to the patientbased on the control signal generated by the respiration processor.

A system according to the present invention may include one or more ofthe features, structures, methods, or combinations thereof describedherein. For example, a cardiac monitor, cardiac stimulator, drug pump,or other type of implantable, partially implantable or patient-externalmedical device may be implemented to include one or more of theadvantageous features and/or processes described above. It is intendedthat such an implanted, partially implanted or patient external deviceneed not include all of the features described herein, but may beimplemented to include selected features that provide for usefulstructures and/or functionality. Such a device may be implemented toprovide a variety of therapeutic or diagnostic functions.

The implementation described in connection with FIG. 9 presumes thatmeasurement of respiration characteristics, estimation of respirationcharacteristics, determination of respiration metrics and developingrespiration trends is performed within an implantable device. In otherconfigurations, these processes may be performed by the remote device965, which may comprise a patient-external device, or by two or moreimplantable or patient-external devices that are communicativelycoupled. For example, in one configuration, the implantable device 960may perform one subset of the functions described above and the remotedevice 965, which may be a device programmer or advanced patientmanagement system, may perform another subset of the functions.

Various modifications and additions can be made to the preferredembodiments discussed hereinabove without departing from the scope ofthe present invention. For example, the methods and systems describedherein generally include an implantable device or sensor for sensingrespiratory characteristics and/or computing a patient's respirationrate and/or respiration rate distribution. It is understood that methodsand systems of the present invention may be implemented usingpatient-external devices and sensors, and that the embodiments describedherein may be implemented in the context of such patient-externaldevices and sensors. Accordingly, the scope of the present inventionshould not be limited by the particular embodiments described above, butshould be defined only by the claims set forth below and equivalentsthereof.

What is claimed is:
 1. A method of determining one or more respirationmetrics, comprising: generating a signal indicative of respiration of apatient using one or more sensors; receiving the signal indicative ofrespiration in an implantable device and determining, for each apertureof a plurality of shorter time apertures and for each aperture of aplurality of longer time apertures, an estimated characteristic of therespiration of the patient based on the respiration signal; and theimplantable device determining one or more respiration metrics using oneor both of the estimated respiration characteristics of the plurality ofshorter time apertures and the estimated respiration characteristics ofthe plurality of longer time apertures, wherein determining the one ormore respiration metrics includes determining a maximum respirationmetric based on the estimated characteristics for each of the pluralityof shorter time apertures and determining a minimum respiration metricbased on the estimated characteristics of each of the plurality oflonger time apertures.
 2. The method of claim 1, wherein determining theestimated respiration characteristic for each aperture comprises:measuring a respiration characteristic for each breath cycle of theaperture; and determining the estimated respiration characteristic forthe aperture based on the measured respiration characteristics.
 3. Themethod of claim 2, wherein determining the estimated respirationcharacteristic for the aperture comprises determining the estimatedrespiration characteristic based on a median value of the measuredrespiration characteristics.
 4. The method of claim 1, whereindetermining the estimated respiration characteristic for each aperturecomprises determining an estimated respiration rate for each aperture.5. The method of claim 1, wherein at least one of generating the signal,determining the estimated characteristic, and determining the one ormore respiration metrics is performed at least in part by theimplantable device.
 6. The method of claim 1, wherein: determining theestimated respiration characteristic for each of the plurality ofshorter time apertures comprises determining a maximum respiration ratefor each of the plurality of shorter time apertures; determining theestimated respiration characteristic for each of the plurality of longertime apertures comprises determining a minimum respiration rate for eachof the plurality of longer time apertures; and determining therespiration metrics comprises determining a daily maximum respirationrate using the maximum respiration rates of the plurality of shortertime apertures and determining a daily minimum respiration rate usingthe minimum respiration rates of the plurality of longer time apertures.7. The method of claim 1, further comprising developing a trend using atleast one of the estimated respiration characteristics determined forthe plurality of shorter time apertures, the estimated respirationcharacteristics determined for the plurality of longer time apertures,and the one or more respiration metrics.
 8. The method of claim 1,further comprising detecting a presence of a disease or disorder usingat least one of the estimated respiration characteristics determined forthe plurality of shorter time apertures, the estimated respirationcharacteristics determined for the plurality of longer time apertures,and the one or more respiration metrics.
 9. The method of claim 1,further comprising tracking progression of heart failure using at leastone of the estimated respiration characteristics determined for theplurality of shorter time apertures, the estimated respirationcharacteristics determined for the plurality of longer time apertures,and the one or more respiration metrics.
 10. The method of claim 9,further comprising initiating, modifying or terminating therapy based onthe heart failure progression.
 11. The method of claim 10, wherein thetherapy includes a cardiac pacing therapy.
 12. The method of claim 1,wherein at least some of the plurality of shorter time apertures overlapeach other.
 13. The method of claim 1, wherein at least some of theplurality of longer time apertures overlap each other.
 14. A method,comprising: generating a signal indicative of respiration of a patientusing one or more sensors; receiving the signal indicative ofrespiration in an implantable device; the implantable devicedetermining, for each aperture of a plurality of shorter time aperturesand for each aperture of a plurality of longer time apertures, anestimated characteristic of the respiration based on the respirationsignal; the implantable device determining one or more respirationmetrics using one or both of the estimated respiration characteristicsof the plurality of shorter time apertures and the estimated respirationcharacteristics of the plurality of longer time apertures, whereindetermining the one or more respiration metrics includes determining amaximum respiration metric based on the estimated characteristics foreach of the plurality of shorter time apertures and determining aminimum respiration metric based on the estimated characteristics ofeach of the plurality of longer time apertures; the implantable deviceidentifying spurious respiration cycles associated with cardiacactivity; and the implantable device excluding the spurious respirationcycles when determining the estimated respiration characteristic. 15.The method of claim 14, wherein determining the estimated respirationcharacteristic for each aperture comprises determining an estimatedrespiration rate for each aperture.
 16. The method of claim 14, wherein:determining the estimated respiration characteristic for each of theplurality of shorter time apertures comprises determining a maximumrespiration rate for each of the plurality of shorter time apertures;determining the estimated respiration characteristic for each of theplurality of longer time apertures comprises determining a minimumrespiration rate for each of the plurality of longer time apertures; anddetermining the respiration metrics comprises determining a dailymaximum respiration rate using the maximum respiration rates of theplurality of shorter time apertures and determining a daily minimumrespiration rate using the minimum respiration rates of the plurality oflonger time apertures.
 17. A method, comprising: generating a signalindicative of respiration of a patient using one or more sensors;receiving the signal indicative of respiration in an implantable deviceand determining, for each aperture of a plurality of shorter timeapertures and for each aperture of a plurality of longer time apertures,an estimated characteristic of the respiration based on the respirationsignal; and the implantable device determining one or more respirationmetrics using one or both of the estimated respiration characteristicsof the plurality of shorter time apertures and the estimated respirationcharacteristics of the plurality of longer time apertures, whereindetermining the one or more respiration metrics includes determining amaximum respiration metric based on the estimated characteristics foreach of the plurality of shorter time apertures and determining aminimum respiration metric based on the estimated characteristics ofeach of the plurality of longer time apertures and wherein at least someof the plurality of shorter time apertures overlap each other and atleast some of the plurality of longer time apertures overlap each other.18. The method of claim 17, wherein: determining the estimatedrespiration characteristic for each of the plurality of shorter timeapertures comprises determining a maximum respiration rate for each ofthe plurality of shorter time apertures; determining the estimatedrespiration characteristic for each of the plurality of longer timeapertures comprises determining a minimum respiration rate for each ofthe plurality of longer time apertures; and determining the respirationmetrics comprises determining a daily maximum respiration rate using themaximum respiration rates of the plurality of shorter time apertures anddetermining a daily minimum respiration rate using the minimumrespiration rates of the plurality of longer time apertures.
 19. Amethod of determining one or more respiration metrics, comprising:generating a signal indicative of respiration of a patient using one ormore sensors; receiving the signal indicative of respiration in animplantable device and determining, for each aperture of a plurality ofshorter time apertures and for each aperture of a plurality of longertime apertures, an estimated characteristic of the respiration based onthe respiration signal; the implantable device determining one or morerespiration metrics using one or both of the estimated respirationcharacteristics of the plurality of shorter time apertures and theestimated respiration characteristics of the plurality of longer timeapertures, wherein the estimated respiration characteristic of eachshorter time aperture includes a median value of respiration ratesmeasured during the shorter time aperture and the estimated respirationcharacteristic of each longer time aperture includes a median value ofrespiration rates measured during the longer time aperture and whereindetermining the respiration metrics includes determining a maximum ofthe median values of the respiration rates measured for each of theplurality of shorter time apertures and determining a minimum of themedian values of the respiration rates measured for each of theplurality of longer time apertures.
 20. The method of claim 19, furthercomprising: determining a daily maximum respiration rate using themaximum of the median values of the respiration rates for each of theplurality of shorter time apertures and determining a daily minimumrespiration rate using the minimum of the median values of therespiration rates for each of the plurality of longer time apertures.